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Jupyter VS Microsoft Azure

Compare Jupyter VS Microsoft Azure and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Microsoft Azure logo Microsoft Azure

Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Microsoft Azure Landing page
    Landing page //
    2023-04-10

Jupyter features and specs

  • Interactive Computing
    Jupyter allows real-time interaction with the data and code, providing immediate feedback and making it easier to experiment and iterate.
  • Rich Media Output
    It supports output in various formats including HTML, images, videos, LaTeX, and more, enhancing the ability to visualize and interpret results.
  • Language Agnostic
    Jupyter supports multiple programming languages through its kernel system (e.g., Python, R, Julia), allowing flexibility in the choice of tools.
  • Collaborative Features
    It enables collaboration through shared notebooks, version control, and platform integrations like GitHub.
  • Educational Tool
    Jupyter is widely used for teaching, thanks to its easy-to-use interface and ability to combine narrative text with code, making it ideal for assignments and tutorials.
  • Extensibility
    Jupyter is highly extensible with a large ecosystem of plugins and extensions available for various functionalities.

Possible disadvantages of Jupyter

  • Performance Issues
    For larger datasets and more complex computations, Jupyter can be slower compared to running scripts directly in a dedicated IDE.
  • Version Control Challenges
    Managing version control for Jupyter notebooks can be cumbersome, as they are not plain text files and include metadata that can make diffing and merging complex.
  • Resource Intensive
    Running Jupyter notebooks can be resource-intensive, especially when working with multiple large notebooks simultaneously.
  • Security Concerns
    Because Jupyter allows code execution in the browser, it can be a potential security risk if notebooks from untrusted sources are run without restrictions.
  • Dependency Management
    Managing dependencies and ensuring that the notebook runs consistently across different environments can be challenging.
  • Less Suitable for Production
    Jupyter is often considered more as a research and educational tool rather than a production environment; transitioning from a notebook to production code can require significant refactoring.

Microsoft Azure features and specs

  • Scalability
    Azure offers a highly scalable environment where you can easily adjust compute resources to match your needs.
  • Global Reach
    Azure has multiple data centers around the globe, providing extensive global coverage for applications and services.
  • Integration with Microsoft Products
    Azure integrates seamlessly with existing Microsoft software like Office 365, Active Directory, and Windows Server.
  • Compliance
    Azure adheres to a broad set of international standards and compliance certifications, including GDPR, ISO, and many others.
  • Service Offerings
    Azure provides a wide variety of services, from virtual machines to databases and AI-powered functionalities.
  • Hybrid Solutions
    Azure supports hybrid cloud configurations, allowing businesses to run some resources on-premises and some in the cloud.
  • Security
    Azure employs advanced security protocols and has multiple layers of security, including data encryption and secure access controls.

Possible disadvantages of Microsoft Azure

  • Cost Management
    The pricing structure can be complex and may lead to unexpected costs if not carefully managed.
  • Learning Curve
    New users may find Azure challenging to learn due to its extensive range of services and configurations.
  • Service Limits
    Some Azure services have limitations and quotas, which can hinder performance or scalability if reached.
  • Support Costs
    While Azure offers robust support, advanced support plans can be expensive.
  • Complexity in Hybrid Setup
    Setting up and managing a hybrid environment can be technically challenging and may require specialized skills.
  • Downtime Risks
    Although rare, Azure is not immune to outages and downtime, which can impact service availability.
  • Data Migration
    Migrating data and services into Azure can be complicated and may require significant planning and resources.

Jupyter videos

+ Add

What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

Microsoft Azure videos

+ Add

Building your first Azure Blockchain Workbench application

More videos:

  • Review - How does Microsoft Azure work?
  • Review - Introduction to Azure Blockchain Workbench
  • Review - Microsoft Azure Overview
  • Tutorial - What Is Azure? | Microsoft Azure Tutorial For Beginners | Microsoft Azure Training | Simplilearn
  • Review - Bots and Azure Blockchain Workbench

Category Popularity

0-100% (relative to Jupyter and Microsoft Azure)

Jupyter

Microsoft Azure

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Cloud Computing
0 0%
Cloud Computing
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Cloud Infrastructure
0 0%
Cloud Infrastructure
100% 100

User comments

Share your experience with using Jupyter and Microsoft Azure. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Jupyter and Microsoft Azure

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

Microsoft Azure Reviews

Top 15 MuleSoft Competitors and Alternatives
The Azure API Management platform has over a million APIs for modernizing legacy apps to adopting API-first strategies from on-premises to multi-cloud. Thousands of the world’s largest enterprises use the solution to build, secure, and scale API initiatives.
Source: bstrategyhub.com
20 Best Free Website Hosting (July 2023)
New users can usually receive a free site credit at the largest cloud services like Microsoft Azure, Amazon Web Services, and Google Cloud Platform to get started. However, when these free credits expire, cloud products can be quite expensive and out of the price range of many projects.
Source: www.hostingadvice.com
AWS vs Azure Which is best for your career?
This course provides the key knowledge required to prepare for Exam AZ-204: Developing Solutions for Microsoft Azure. You will learn how to develop and deploy cloud applications on Azure using various Azure services.
Source: www.netcomlearning.com
Top 10 Best Container Software in 2022
Tool Cost/Plan Details: There is no upfront cost. Azure does not charge for cluster management. It charges only for what you use. It has Pricing for nodes model. Based on your container needs, you can get the price estimator through Container Services calculator.
Source: www.softwaretestinghelp.com
Top 50 Cheapest Cloud Services Providers | Affordable Cloud Hosting
With direct competitors like AWS, Microsoft Azure has been one of the most preferred and also cheapest cloud services providers. The plan that Azure submit depends on the services a business seeks to access. Azure cloud platform includes over 200 products and cloud services to assist businesses in bringing new solutions to life—to solve today’s challenges and create the...
Source: makeanapplike.com

Social recommendations and mentions

Based on our record, Jupyter should be more popular than Microsoft Azure. It has been mentiond 216 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Jupyter mentions (216)

  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / about 2 months ago
  • LangChain: From Chains to Threads
    LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 3 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 4 months ago
  • Jupyter Notebook for Java
    Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 8 months ago
  • JIRA Analytics with Pandas
    One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 11 months ago
View more

Microsoft Azure mentions (66)

  • How to Develop a Voice Chatbot
    Microsoft Azure offers a Bot Framework with built-in support for voice interactions via the Speech SDK. - Source: dev.to / 9 months ago
  • Setting Up a Windows 11 Virtual Machine with Azure on a MacOs
    The first step in creating a virtual machine is getting a Microsoft account. Once you have a Microsoft account click this link to create an Azure free trial account. Click on the "Try Azure for free" button. This takes you to the page below. - Source: dev.to / about 1 year ago
  • How To Create Windows 11 Virtual Machine in Azure
    Before you start, ensure you have an active Azure subscription, if you don't have one, Click here to create a free account. - Source: dev.to / about 1 year ago
  • The 2024 Web Hosting Report
    A VM is the original “hosting” product of the cloud era. Over the last 20 years, VM providers have come and gone, as have enterprise virtualization solutions such as VMware. Today you can do this somewhere like OVHcloud, Hetzner or DigitalOcean, which took over the “server” market from the early 2000’s. Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft's Azure also offer VMs, at a less... - Source: dev.to / over 1 year ago
  • Deploying flask app to Kubernetes using Minikube
    Before deploying the application with Kubernetes, you need to containerize the application using docker. This article shows how to deploy a Flask application on Ubuntu 22.04 using Minikube; a Kubernetes tool for local deployment for testing and free offering. Alternatively, you can deploy your container apps using Cloud providers such as GCP(Google Cloud), Azure(Microsoft) or AWS(Amazon). - Source: dev.to / over 1 year ago
View more

What are some alternatives?

When comparing Jupyter and Microsoft Azure, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.

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